Large organizations with multiple mobile locations, such as governments, hospitals, banks, companies, and universities, carry out services in complex operational settings and process a tremendous amount of day-to-day transactions. Properly managing each level of organizational operations helps the organization as a whole to smoothly function. When organizations have mobile workers or workers at multiple sites, the need to organize and process the data of each worker's daily activities for an operating system for the organization is recognized as all the information regarding the workers' activities conveyed remotely is not timely reflected back to the organizational knowledge base. For example, local governments typically provide a variety of types of public services on a daily basis, including police, fire, emergency services, transportation, and so on. Similarly, hospitals also provide services varying from patient to patient. However, current knowledge base for organizations is not capable of collecting and incorporating all of the data obtained during the performance of their services into the business operations. Thus, the performance of the organizations is not satisfactorily analyzed from the unorganized and unincorporated daily activity data.
Performance of an organization can be evaluated by examining how the organization complies with their purpose and policy. For example, fire departments must quickly respond to unanticipated fire events and they need to use their resources efficiently. Traffic control and parking organizations need to have certain revenues from enforcement activities but also need to balance their activities between enforcement and other public service activities. Workers in hospitals, such as doctors and nurses, need to handle patients who have different health issues in various urgent levels quickly and efficiently with their resources. To properly carry out services in conformity with their purposes and policies, an organization must have a way to track each single activity occurring in real time and to analyze the impacts of the activity in terms of performance as an organization.
Traditionally, to evaluate activities taken by workers in an organization for a certain event, managers or supervisors in the organization first collect information manually from informal notes, calendars, emails, logs, and so on, to review and analyze the organizational performance. Then, they manually organize the activity information to a series to summarize the activities for the event in a report for further analysis. When the managers and supervisors plan for a new event, they first retrospectively examine the impact of past events using the information only from the report at-hand and then forecast future resource demands. Such traditional methods do not provide convenient ways of collecting, organizing, reviewing, or planning of the event data.
Although the activity data can be digitally encoded and retrospectively maintained in a database, association with events has not been easily made. The events are episodic data that can happen at a given place and time. The events can include accidents, fires, storms, sporting events, film projects, or health care for patients in the hospital. Thus, the events can be planned or unplanned, and may last for various periods of time.
Typically, organizations respond to an event and take actions as the event unfolds, but data regarding the activities performed by the organizations are recorded into a certain database without satisfactory association with the events. Thus, the organizational activity data related to a particular event cannot be readily distinguished from other organizational activity data and analysis particular to each event or class of events is impracticable. Further, when analyzing the events to understand the organizational performance, a lack of data regarding activities by workers for the events causes incomplete comprehension of each event or events as a whole. In other words, each event cannot be fully analyzed for characterization or modeling, which is important for managing organizational operations.
Thus, there is a need for collecting real-time organizational activity data in association with an event and efficiently and accurately analyzing performance of the organization from the collected organizational activity data for the event.